Telehealth as a Component of One Health: a Position Paper
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: One Health (OH) refers to the integration of human, animal, and ecosystem health within one framework in the context of zoonoses, antimicrobial resistance and stewardship, and food security. Telehealth refers to distance delivery of healthcare. A systems approach is central to both One Health and telehealth, and telehealth can be a core component of One Health. Here we explain how telehealth might be integrated into One Health. METHODS: We have considered antimicrobial resistance (AMR) as a use case where both One Health and telehealth can be used for coordination among the farming sector, the veterinary services, and human health providers to mitigate the risk of AMR. We conducted a narrative review of the literature to develop a position on the inter-relationships between telehealth and One Health. We have summarised how telehealth can be incorporated within One Health. RESULTS: Clinicians have used telehealth to address antimicrobial resistance, zoonoses, food borne infection, improvement of food security and antimicrobial stewardship. We identified little existing evidence in support of the usage of telehealth within a One Health paradigm, although in isolation, both are useful for the same purpose, i.e., mitigation of the significant public health risks posed by zoonoses, food borne infections, and antimicrobial resistance. CONCLUSIONS: It is possible to integrate telehealth within a One Health framework to develop effective inter-sectoral communication essential for the mitigation and addressing of zoonoses, food security, food borne infection containment and antimicrobial stewardship. More research is needed to substantiate and investigate this model of healthcare.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it